The present invention improves upon current mobile and visual advertisements and marketing services. Currently available online marketing services use ads created for large demographics, or if geared towards individual users, are generated by analyzing written or demographic surveys as well as other methods of targeting interested and relevant customers. The same is true with commercial advertising on TV. Aggregate demographic data is used in conjunction with applicable metadata, categorical or qualitative data on a particular user or household, in an attempt to create a more user unique, individualized marketing experience. Typically, collected data is used to create a profile of mobile users or potential viewers to determine appropriate advertisements or conversely the data is used in the plurality and an advertisement is directed towards a large demographic rather than individuals.
One of the problems we solve for with our method is creating an ad aesthetically appealing to consumers individually on an individualized global scale, reducing the time it takes to generate an appropriate profile for individual users under existing methods and the method by which the subsequent advertisement is then created. Mobile ads need to be location and time sensitive and while mobile marketing methods increase the conversion of data into a relevant advertising experience for users, we teach that our method is clearly advantageous and unique to current profiling done by large marketing firms or similar corporate giants such as Facebook. In addition, current mobile advertising using Web Banners or Mobile Web Posters have shown to be rather ineffective at enriching the users experience and providing advertisers with increase flow rate, “click-through”, used to determine the effectiveness and subsequent value of the ad. As such the industry has relied on SMS, short message service, advertising rather than visual, more traditionally based, advertising, to drive revenue growth as the creation of individual specific, targeted Web Banners has proved less than ideal from a return on investment perspective.
This limitation is mainly due to the difficulty in creating ads targeted to individual, unique users and the limited space available in which to place the advertisements on mobile devices. Currently many large corporations are expending ever-increasing amounts of capital on the issue of maximizing target specific mobile advertising. We teach that a marriage of emerging technology and traditional advertising paradigms can have a significant positive impact on “click-through” rates and market adoption of our unique method.
Conventional Visual Advertising attraction is based upon many factors, including but not limited to aesthetic appeal of the model used in the advertisement. This aesthetic appeal will vary between each individual consumer, and as such traditional methods utilize aggregate data in creating average profiles for consumers in a specified local or demographic. Alternatively, target specific ads are currently generated by mining user choices and responses to written and or visual surveys with the hope of determining an individual marketing profile for each user. While this is obviously superior to aggregate demographic marketing it still leaves the question of an individual user's personal preference in terms of aesthetic appeal to debate considering the amount and variety of data that are used in determining currently placed ads.
We teach that by using binomial logistic regression to create an attraction model determined by recording the user's choices of thumbnail or other facial pictures amongst a field of such images, one can then determine a baseline aesthetic attraction model for each individual user of the mobile device without the need for any additional aggregate data or written surveys and analysis. While at the same time the addition of non-aesthetic, existing profile data and that derived from the method herein; should further enhance results.
One explanation for this increase in individual consumer appeal, is that the use of un-prompted choices amongst multiple options provides a view into the subconscious of mobile users and creates a marketing profile and model of aesthetic attraction that is free of potential influences and detractions that can enter into the profile by using written commands or prompts.
Aesthetic attraction is potentially the most important component of visual advertising. Understanding and shaping a mobile user's unique profile should be deconstructed so that different variables such as number of choices per page, number of same choices, time between choices, and other variables must be taken into account when building a user's individual aesthetic appeal model. We teach that the mobile internet, in particular phones and tablets, already provide the perfect medium for recording these choices in existing online dating sites. Many mobile dating applications, such as Grinder and Growler, utilize multiple facial thumbnails on a page or field in which the user, unprompted, by nature of the site touches on images, that from the minimal perspective of mobile media, appeal to the user's individual taste or attraction.
This allows for the uninhibited, subconscious choices of mobile users to be recorded, attraction profiles/models to be constructed and user specific mobile advertisements to be generated and populated on the screen of said user's mobile device.
The method of the present invention is designed to provide a model of a mobile user's aesthetic preference which can then, in turn, be used to populate ads which have a mathematical superior confidence interval of attracting a mobile phone user's attention; due to aesthetic appeal, hence promoting click-trough's and increased interest in otherwise potential generic advertisements.